Jonathan W. Siegel
Orcid: 0000-0002-1493-4889
According to our database1,
Jonathan W. Siegel
authored at least 28 papers
between 2018 and 2024.
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Collaborative distances:
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Bibliography
2024
Sharp Bounds on the Approximation Rates, Metric Entropy, and n-Widths of Shallow Neural Networks.
Found. Comput. Math., April, 2024
J. Complex., 2024
Approximation Rates for Shallow ReLU<sup>k</sup> Neural Networks on Sobolev Spaces via the Radon Transform.
CoRR, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
J. Comput. Phys., July, 2023
Optimal Approximation Rates for Deep ReLU Neural Networks on Sobolev and Besov Spaces.
J. Mach. Learn. Res., 2023
A qualitative difference between gradient flows of convex functions in finite- and infinite-dimensional Hilbert spaces.
CoRR, 2023
Optimal Approximation of Zonoids and Uniform Approximation by Shallow Neural Networks.
CoRR, 2023
Sharp Lower Bounds on Interpolation by Deep ReLU Neural Networks at Irregularly Spaced Data.
CoRR, 2023
2022
IEEE Trans. Inf. Theory, 2022
CoRR, 2022
CoRR, 2022
2021
CoRR, 2021
CoRR, 2021
CoRR, 2021
2020
Neural Networks, 2020
Multiscale Model. Simul., 2020
High-Order Approximation Rates for Neural Networks with ReLU<sup>k</sup> Activation Functions.
CoRR, 2020
2019
2018